Abstract
Traffic congestion problems of urban road networks are having a strong impact on economy, due to losses from accidents and delays, and to public health. The recent progress in connected vehicles is expanding the approaches that can be exploited to tackle traffic congestion, particularly in urban regions. Connected vehicles pave the way to centralised real-time re-routing, where a urban traffic controller can suggest alternative routes to be followed in order to reduce delays and mitigate congestion issues in the network. In this work, we introduce a centralised architecture and we compare in simulation a number of approaches that can be exploited for re-routing vehicles.
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Acknowledgement
Mauro Vallati was partially funded by the EPSRC grant EP/R51343X/1 (AI4ME). Lukáš Chrpa was partially funded by the Czech Science Foundation (project no. 18-07252S).
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Vallati, M., Chrpa, L. (2020). Reducing Traffic Congestion in Urban Areas via Real-Time Re-Routing: A Simulation Study. In: Gallagher, M., Moustafa, N., Lakshika, E. (eds) AI 2020: Advances in Artificial Intelligence. AI 2020. Lecture Notes in Computer Science(), vol 12576. Springer, Cham. https://doi.org/10.1007/978-3-030-64984-5_6
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DOI: https://doi.org/10.1007/978-3-030-64984-5_6
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